P-value Correction Research Articles

Reliability of self-reported dispositional mindfulness scales and their association with working memory performance and functional connectivity

We systematically investigated the link between trait mindfulness scores and functional connectivity (FC) features or behavioral data, to emphasize the importance of the reliability of self-report mindfulness scores. Sixty healthy young male participants underwent two functional MRI runs with three mindfulness or mind-wandering task blocks with an N-back task (NBT) block. The data from 49 participants (age: 23.3 ± 2.8) for whom two sets of the self-reported Mindfulness Attention Awareness Scale (MAAS) and NBT performance were available were analyzed. We divided participants into two groups based on the consistency level of their MAAS scores (i.e., a “consistent” and an “inconsistent” group). Then, the association between the MAAS scores and FC features or NBT performance was investigated using linear regression analysis with p-value correction and bootstrapping. Meaningful associations (a) between MAAS and NBT accuracy (slope = 0.41, CI = [0.10, 0.73], corrected p < 0.05), (b) between MAAS and the FC edges in the frontoparietal network, and (c) between the FC edges and NBT performance were only observed in the consistent group (n = 26). Our findings demonstrate the importance of appropriate screening mechanisms for self-report-based dispositional mindfulness scores when trait mindfulness scores are combined with neuronal features and behavioral data.

Sex-Related Disparities in Acute Limb Ischemia Treatment Outcomes

Although a substantial impetus behind disparities research in healthcare exists, those that are sex-related within vascular surgery outcomes are largely unexplored. Consequently, published guidelines lack specificity when it comes to treating male and female patients with vascular disease. Disparities related to patients suffering from chronic limb-threatening ischemia have been broached, although no extensive studies assessing disparities in acute limb ischemia treatment outcomes have come to the forefront. In this study, our aim is to identify and quantify sex-related disparities as they pertain to interventions for acute limb ischemia. Using the TriNetX global research network, we conducted a multicenter query across 48 healthcare organizations spanning five countries for patients treated for acute limb ischemia. We determined the number of male and female patients that received one of the following interventions: open revascularization, percutaneous mechanical thrombectomy, or catheter-directed thrombolysis and/or adjunctive endovascular procedures. Propensity score matching was performed to account for comorbidities. Risk of adverse outcomes within 30 days was calculated for each sex, including re-intervention, major amputation, and death. Risk of adverse outcomes was then compared between treatment groups of the same sex and between sexes. Type I errors were reduced through utilization of the Holm-Bonferroni method to correct P-values. Within our study we noted several important findings. Females were more likely to receive catheter-directed thrombolysis and/or adjunctive endovascular procedures (p = 0.001) than males. There were no significant differences in the rates of open revascularization or percutaneous mechanical thrombectomy between males and females. Overall, females were more likely to die within 30 days (p < 0.0001) and greater number of males required reintervention within 30 days (p < 0.0001). Analyzing outcomes within individual treatment groups, females undergoing open revascularization or catheter-directed thrombolysis and/or adjunctive endovascular intervention demonstrated a profound increase in mortality within 30 days of intervention (p = 0.0072 and p = 0.0206, respectively), but these differences were not reflected in the percutaneous mechanical thrombectomy group. Limb salvage rates in females were higher than males overall although there were no significant sex differences within any treatment groups specifically. In conclusion, there was a significantly higher risk of death in females across all treatment groups in the studied timeframe. Limb salvage rates were higher for females in the OR treatment group, while males were more likely to require a reintervention across all treatment groups. By evaluating these disparities, we can provide greater insight into personalized treatment for patients presenting with acute limb ischemia.

Selective Breeding for High Intrinsic Exercise Capacity Slows Pan-Tissue Epigenetic Aging in Rats

Aerobic exercise capacity is strongly associated with longevity and reduction in all-cause mortality. Rats selectively bred for high intrinsic running capacity (HCR) compared with low (LCR), have between a 28-45% increase in median lifespan. It is not known whether the greater HCR survival is associated with slowed epigenetic aging. We hypothesized that HCR rats would express altered rates of pan-tissue DNA methylation corresponding to a slowed epigenetic clock (DNAmAge). Male and female LCR and HCR rats from generation 15-17 (n=22; chronological age=2.34±0.45 yrs (mean±SD)), generation 28 (n=20; 1.09±0.05 yrs) and generation 37 (n=20; 1.04±0.08 yrs) were included. DNA was extracted from skeletal muscle (n=61), cardiac muscle (n=60), adipose (n=61) and liver (n=61). DNAmAge was quantitated using the mammalian methylation array platform (~106k CpGs specific to brown rat). Three epigenetic clocks were used, previously trained on separate rat tissues, including dual species clocks that apply to rats and humans (pan-tissue rat clock; human-rat clocks for relative and chronologic age). Slowing of epigenetic age relative to chronologic age was assessed by multivariable regression adjusted for chronologic age, generation, sex and phenotype (treadmill running distance at 3 months of age). Epigenome wide association with phenotype was performed in Limma, with Benjamini-Hochberg p-value correction and significance set at FDR q&lt;0.05. Gene set enrichment analysis was performed with Gene Ontology Biological Processes. Maximum treadmill running distance was ~8 times greater in HCR than LCR (2,137±500 vs. 246±63 m; p=1.97✕10-20). Across all samples and clocks, epigenetic age was associated with chronological age (r=0.461-0.500; p&lt;3.60✕10-14). Compared with LCR, HCR epigenetic aging was slowed by a mean of -0.18 to -0.24 yrs, which represents 9-42% lower DNAmAge in HCR rats than LCR (p&lt;0.024). Tissue-specific analyses revealed a lower DNAmAge in HCR for adipose, skeletal muscle and cardiac muscle (pan-tissue rat clock; p&lt;0.04), and liver (human-rat clock for relative and chronologic age; p&lt;0.01); effects were strongest at younger chronologic age. Significantly differentially methylated CpGs were found in skeletal muscle (n=11,341), cardiac muscle (n=2,480), adipose (n=3,036) and liver (n=12,595). Of the top 10 differentially methylated pathways, ~58% related to tissue development and ~20% related to cardiac or skeletal muscle. These data show differences in the rate of epigenetic aging manifest in tissues that directly (skeletal and cardiac muscle) and indirectly (adipose, liver) contribute to the energy transfer of aerobic exercise capacity upon which the selective breeding of LCR and HCR rat models were based. These data suggest that a large fraction of the survival benefit associated with high intrinsic exercise capacity is reflected in slowed epigenetic aging across multiple tissues. The Lundquist Institute. Epigenetic Clock Development Foundation. The University of Toledo Department of Physiology &amp; Pharmacology. NIH (R01HL151452, R01HL153460, P50HD098593, P40OD021331). Open Philanthropy (SH). This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Retinal thickness as a biomarker of cognitive impairment in manifest Huntington’s disease

BackgroundCognitive decline has been reported in premanifest and manifest Huntington’s disease but reliable biomarkers are lacking. Inner retinal layer thickness seems to be a good biomarker of cognition in other neurodegenerative diseases.ObjectiveTo explore the relationship between optical coherence tomography-derived metrics and global cognition in Huntington’s Disease.MethodsThirty-six patients with Huntington’s disease (16 premanifest and 20 manifest) and 36 controls matched by age, sex, smoking status, and hypertension status underwent macular volumetric and peripapillary optical coherence tomography scans. Disease duration, motor status, global cognition and CAG repeats were recorded in patients. Group differences in imaging parameters and their association with clinical outcomes were analyzed using linear mixed-effect models.ResultsPremanifest and manifest Huntington’s disease patients presented thinner retinal external limiting membrane-Bruch’s membrane complex, and manifest patients had thinner temporal peripapillary retinal nerve fiber layer compared to controls. In manifest Huntington’s disease, macular thickness was significantly associated with MoCA scores, inner nuclear layer showing the largest regression coefficients. This relationship was consistent after adjusting for age, sex, and education and p-value correction with False Discovery Rate. None of the retinal variables were related to Unified Huntington’s Disease Rating Scale score, disease duration, or disease burden. Premanifest patients did not show a significant association between OCT-derived parameters and clinical outcomes in corrected models.ConclusionsIn line with other neurodegenerative diseases, OCT is a potential biomarker of cognitive status in manifest HD. Future prospective studies are needed to evaluate OCT as a potential surrogate marker of cognitive decline in HD.

Costs and Benefits of Popular P-Value Correction Methods in Three Models of Quantitative Omic Experiments.

The multiple hypothesis testing problem is inherent in large-scale quantitative "omic" experiments such as mass spectrometry-based proteomics. Yet, tools for comparing the costs and benefits of different p-value correction methods under different experimental conditions are lacking. We performed thousands of simulations of omic experiments under a range of experimental conditions and applied correction using the Benjamini-Hochberg (BH), Bonferroni, and permutation-based false discovery proportion (FDP) estimation methods. The tremendous false discovery rate (FDR) benefit of correction was confirmed in a range of different contexts. No correction method can guarantee a low FDP in a single experiment, but the probability of a high FDP is small when a high number and proportion of corrected p-values are significant. On average, correction decreased sensitivity, but the sensitivity costs of BH and permutation were generally modest compared to the FDR benefits. In a given experiment, observed sensitivity was always maintained or decreased by BH and Bonferroni, whereas it was often increased by permutation. Overall, permutation had better FDR and sensitivity than BH. We show how increasing sample size, decreasing variability, or increasing effect size can enable the detection of all true changes while still correcting p-values, and we present basic guidelines for omic experimental design. Analysis of an experimental proteomic data set with defined changes corroborated these trends. We developed an R Shiny web application for further exploration and visualization of these models, which we call the Simulator of P-value Multiple Hypothesis Correction (SIMPLYCORRECT) and a high-performance R package, permFDP, for easy use of the permutation-based FDP estimation method.

Prog-Plot - a visual method to determine functional relationships for false discovery rate regression methods.

Multiple test corrections are a fundamental step in the analysis of differentially expressed genes, as the number of tests performed would otherwise inflate the false discovery rate (FDR). Recent methods for P-value correction involve a regression model in order to include covariates that are informative of the power of the test. Here, we present Progressive proportions plot (Prog-Plot), a visual tool to identify the functional relationship between the covariate and the proportion of P-values consistent with the null hypothesis. The relationship between the proportion of P-values and the covariate to be included is needed, but there are no available tools to verify it. The approach presented here aims at having an objective way to specify regression models instead of relying on prior knowledge.

Increasing reproducibility, robustness, and generalizability of biomarker selection from meta-analysis using Bayesian methodology.

A major limitation of gene expression biomarker studies is that they are not reproducible as they simply do not generalize to larger, real-world, heterogeneous populations. Frequentist multi-cohort gene expression meta-analysis has been frequently used as a solution to this problem to identify biomarkers that are truly differentially expressed. However, the frequentist meta-analysis framework has its limitations-it needs at least 4-5 datasets with hundreds of samples, is prone to confounding from outliers and relies on multiple-hypothesis corrected p-values. To address these shortcomings, we have created a Bayesian meta-analysis framework for the analysis of gene expression data. Using real-world data from three different diseases, we show that the Bayesian method is more robust to outliers, creates more informative estimates of between-study heterogeneity, reduces the number of false positive and false negative biomarkers and selects more generalizable biomarkers with less data. We have compared the Bayesian framework to a previously published frequentist framework and have developed a publicly available R package for use.

1192-P: Diabetes-Related Proteomic Alterations: The Atherosclerosis Risk in Communities (ARIC) Study

Introduction: There is a paucity of large-scale data from multiethnic populations on proteomic alterations related to type 2 diabetes, which could help identify prognostic mediators. Method: We analyzed 4,955 plasma proteins using SomaLogic v4.0 on 10,478 ARIC Study participants (Visit 2, 1990-92, mean age: 57±6 years, 56% women, 22% Black adults, 14% with diabetes) . We used logistic regression to quantify proteins associations with prevalent diabetes in a 2/3 discovery and 1/3 validation subset, with Bonferroni correction of P-values. Results: After adjustment for demographics, clinical, and lifestyle risk factors (Figure) , 642 proteins were significantly associated with diabetes in the discovery sample (p&amp;lt;10−6) , with 3confirmed in the validation sample (p&amp;lt;0.05/642) . The top five findings were semaphorin-6A, plexin-B2, inactive tyrosine-protein kinase 7, cartilage intermediate layer protein 2, and semaphorin-6B. Proteins with known diabetes associations were also identified : insulin receptor, insulin-like growth factor-binding protein 2, growth differentiation factor-15, and adiponectin. Conclusions: A large-scale proteomics approach identified numerous diabetes-related alterations. Pathway analysis and comparison to proteomic risk factors for diabetes incidence and complications will shed light on plasma proteomic consequences of diabetes and their relation to future risk. Disclosure J.B.Echouffo tcheugui: None. P.Lutsey: None. M.Grams: None. E.Selvin: Other Relationship; Wolters Kluwer. J.Coresh: Consultant; Healthy.io Ltd, Research Support; National Institutes of Health. J.Chen: None. M.R.Rooney: None. O.Tang: None. C.M.Ballantyne: Consultant; Abbott Diagnostics, Althera Pharmaceuticals, Amarin Corporation, Amgen Inc., Arrowhead Pharmaceuticals, Inc., AstraZeneca, Corvidia Therapeutics, Denka Seiken, ESPERION Therapeutics, Inc., Genentech, Inc., Gilead Sciences, Inc., Illumina, Matinas BioPharma Inc, Merck &amp; Co., Inc., New Amsterdam, Novartis Pharmaceuticals Corporation, Novo Nordisk, Pfizer Inc., Regeneron Pharmaceuticals Inc., Roche Diagnostics, Sanofi, Research Support; Abbott Diagnostics, Akcea Therapeutics, Amgen Inc., Arrowhead Pharmaceuticals, Inc., ESPERION Therapeutics, Inc., Ionis Pharmaceuticals, Novartis Pharmaceuticals Corporation, Regeneron Pharmaceuticals Inc., Roche Diagnostics. E.Boerwinkle: None. C.E.Ndumele: None. J.S.Pankow: None. R.Demmer: None. Funding National Institutes of Health (K23 HL153774)

Analysis of patient (pt) withdrawal of consent using 11,993 pts from 58 alliance for clinical trials in oncology trials.

6513 Background: Pt recruitment receives well-deserved attention, but pt retention is also important for trial interpretability and generalizability. We report on trends and predictive factors for withdrawal of pt consent, defined as pt cessation from trial participation for reasons not mandated in the protocol. Methods: Alliance phase II/III trials that enrolled pts during 2013 – 2019 were included. All pts had ≥2 years (yrs) of follow-up. Primary outcome was withdrawn consent (yes; no) within 2 yrs of enrollment. Pt factors included year of enrollment, age, race, ethnicity, and gender. Trial factors included randomization, use of placebo, and use of radiation. Univariable (Uni) and full multivariable (MV) logistic regression models (including all factors from Uni setting) with a Bonferroni p-value correction (p &lt;.004 considered significant) were used. Results: Median age was 62 yrs, with 67% female, 82% White, 9% Black or African American, and 7% Hispanic. 52% of trials were phase II, 5% II/III and 43% III. Common (&gt; 10%) trial categories included 22% experimental therapeutics or rare tumors, 12% gastrointestinal, 12% genitourinary, 12% neuro-oncology and 10% symptom intervention. 78% of trials were randomized, 22% placebo-controlled and 14% used radiation. 1060 (9%) pts withdrew consent within 2 yr of enrollment (range,5.7% -9.8%) during 2013-2019. In Uni models, all trial and pt factors significantly predicted pt withdrawal except age, race, and gender (See table). In MV models, pts of Hispanic origin, and &gt;75 yrs were more likely to withdraw. Trials using radiation had less likelihood of pt withdrawal. Placebo-controlled randomized trials had higher likelihood of withdrawal. Conclusions: Both trial and pt factors contribute to higher rates of pt withdrawal from clinical trials. Understanding these factors will enable investigators to focus on pt education and optimization of trial design to improve pt retention and the overall clinical trial plan. Support: U10CA180821, U10CA180882 [Table: see text]

Bias correction for multiple covariate analysis using empirical bayesian estimation in mixed-effects models for longitudinal data

The naïve empirical Bayes method has been widely used as an ad hoc tool in fitting linear mixed-effect models, which is much computationally efficient than the maximum likelihood estimation method. However, the shrinkage effect of the empirical Bayes method causes bias in the estimates of the fixed effects. Bias-correction has been proposed for the mixed-effects model when only one covariate is present. In this paper, we derive the shrinkage factor of the empirical Bayes predictors of the random effects and the variance-covariance matrix of the corrected estimates when the model has more than one covariate. The empirical Bayes estimates and test statistics are then corrected using the derived factor. Theoretical derivations, simulation studies and a real data application demonstrate the validity of the proposed method in that the corrected estimates are unbiased and the corrected tests have correct p-values.

Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection

Despite impressive state-of-the-art performance on a wide variety of machine learning tasks in multiple applications, deep learning methods can produce over-confident predictions, particularly with limited training data. Therefore, quantifying uncertainty is particularly important in critical applications such as lesion detection and clinical diagnosis, where a realistic assessment of uncertainty is essential in determining surgical margins, disease status and appropriate treatment. In this work, we propose a novel approach that uses quantile regression for quantifying aleatoric uncertainty in both supervised and unsupervised lesion detection problems. The resulting confidence intervals can be used for lesion detection and segmentation. In the unsupervised settings, we combine quantile regression with the Variational AutoEncoder (VAE). The VAE is trained on lesion-free data, so when presented with an image with a lesion, it tends to reconstruct a lesion-free version of the image. To detect the lesion, we then compare the input (lesion) and output (lesion-free) images. Here we address the problem of quantifying uncertainty in the images that are reconstructed by the VAE as the basis for principled outlier or lesion detection. The VAE models the output as a conditionally independent Gaussian characterized by its mean and variance. Unfortunately, joint optimization of both mean and variance in the VAE leads to the well-known problem of shrinkage or underestimation of variance. Here we describe an alternative Quantile-Regression VAE (QR-VAE) that avoids this variance shrinkage problem by directly estimating conditional quantiles for the input image. Using the estimated quantiles, we compute the conditional mean and variance for input image from which we then detect outliers by thresholding at a false-discovery-rate corrected p-value. In the supervised setting, we develop binary quantile regression (BQR) for the supervised lesion segmentation task. We show how BQR can be used to capture uncertainty in lesion boundaries in a manner that characterizes expert disagreement.

Urgent need for consistent standards in functional enrichment analysis.

Gene set enrichment tests (a.k.a. functional enrichment analysis) are among the most frequently used methods in computational biology. Despite this popularity, there are concerns that these methods are being applied incorrectly and the results of some peer-reviewed publications are unreliable. These problems include the use of inappropriate background gene lists, lack of false discovery rate correction and lack of methodological detail. To ascertain the frequency of these issues in the literature, we performed a screen of 186 open-access research articles describing functional enrichment results. We find that 95% of analyses using over-representation tests did not implement an appropriate background gene list or did not describe this in the methods. Failure to perform p-value correction for multiple tests was identified in 43% of analyses. Many studies lacked detail in the methods section about the tools and gene sets used. An extension of this survey showed that these problems are not associated with journal or article level bibliometrics. Using seven independent RNA-seq datasets, we show misuse of enrichment tools alters results substantially. In conclusion, most published functional enrichment studies suffered from one or more major flaws, highlighting the need for stronger standards for enrichment analysis.

The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis

BackgroundMolecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Mycobacterium tuberculosiscomplex (MTBC). We aimed to generate a WHO endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction.MethodsA candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher’s exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation.Findings15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations’ pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs.InterpretationThis first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility testing provides a global standard for resistance interpretation. Its existence should encourage the implementation of molecular diagnostics by National Tuberculosis Programmes.FundingUNITAID, Wellcome, MRC, BMGF.

Susceptibility of TNFAIP8, TNFAIP8L1, and TNFAIP2 Gene Polymorphisms on Cancer Risk: A Comprehensive Review and Meta-Analysis of Case-Control Studies.

Objectives: The TNFAIP8 gene family and TNFAIP2 gene are inextricably linked to an elevated risk of cancer development. This systemic review and meta-analysis seeks to establish the relationship between TNFAIP8 (rs11064, rs1045241, rs1045242, and rs3813308), TNFAIP8L1 (rs1060555), and TNFAIP2 (rs710100 and rs8126) polymorphisms with the risk of cancer. Methods and Materials: A systematic search of multiple databases from January 2022 to April 2022 was used to identify relevant studies. Odds ratios (ORs) with corresponding 95% CI and p-value were calculated to assess the association. Bonferroni correction was performed to correct p-values. Trial sequential analysis (TSA) and in-silico messenger RNA expression were also performed. Review Manager 5.4 software was used for performing this meta-analysis. Results: This study comprised 6909 cancer patients and 7087 healthy participants from 14 studies. Four genetic models of rs11064 (codominant 2 [COD2]: OR = 2.30, p = 7.83 × 10−5; codominant 3 [COD3]: OR = 2.10, p = .0006; recessive model [RM]: OR = 2.24, p = .0001; AC: OR = 1.47, p = .037), two genetic models of rs1045241 (codominant 1 [COD1]: OR = 1.27, p = .009; overdominant model [ODM]: OR = 1.24, p = .018), four genetic models of rs1045242 (COD1: OR = 1.52, p = .005; dominant model (DM): OR = 1.56, p = .002; OD: OR = 1.48, p = .008; AC: OR = 1.48, p = .002), and three genetic models of rs8126 (COD2: OR = 1.41, p = .0005; COD3: OR = 1.44, p = .0002; RM: OR = 1.43, p = .0001) were statistically linked to cancer risk. Only one genetic model of rs1060555 polymorphism showed a significant protective association with cancer (COD2: OR = 0.80, p = .048). The outcomes of TSA also validated the findings of the meta-analysis. Conclusion: This study summarizes that rs11064, rs1045241, and rs1045242 polymorphisms of TNFAIP8 gene and rs8126 polymorphism of TNFAIP2 gene are significantly linked with the risk of cancer development. This meta-analysis was registered at INPLASY (registration number: INPLASY202270073).

The Variants at APOA1 and APOA4 Contribute to the Susceptibility of Schizophrenia With Inhibiting mRNA Expression in Peripheral Blood Leukocytes.

Objective: Abnormal lipid metabolism has a close link to the pathophysiology of schizophrenia (SZ). This study mainly aimed to evaluate the association of variants at apolipoprotein A1 (APOA1) and APOA4 with SZ in a Chinese Han population. Methods: The rs5072 of APOA1 and rs1268354 of APOA4 were examined in a case–control study involving 2,680 patients with SZ from the hospital and 2,223 healthy controls screened by physical examination from the community population. The association was estimated with the odds ratio (OR) and 95% confidence intervals (95% CIs) by logistic regression. The APOA1 and APOA4 messenger RNA (mRNA) in peripheral blood leukocytes were measured by real-time PCR and compared between SZ cases and controls. Serum apoA1 levels were detected by turbidimetric inhibition immunoassay and high-density lipoprotein cholesterol (HDL-C) levels were detected by the homogeneous method. Results: Both of the rs5072 of APOA1 and rs1268354 of APOA4 had statistically significant associations with SZ. After adjustment for age and sex, ORs (95% CIs) of the additive model of rs5072 and rs1268354 were 0.82 (0.75–0.90) and 1.120 (1.03–1.23), and p-values were 3.22 × 10−5 and 0.011, respectively. The association of rs5072 with SZ still presented statistical significance even after Bonferroni correction (p-value×6). SZ patients during the episode presented lower levels of apoA1, HDL-C, mRNA of APOA1 common variants and transcript variant 4, and APOA4 mRNA than controls (p < 0.01) while SZ patients in remission showed a significantly decreased APOA1 transcript variant 3 expression level and increased APOA4 mRNA expression level (p < 0.01). mRNA expression levels of APOA1 transcript variant 4 significantly increased with the variations of rs5072 in SZ during the episode (p trend = 0.017). After the SZ patients received an average of 27.50 ± 9.90 days of antipsychotic treatment, the median (interquartile) of serum apoA1 in the SZ episode significantly increased from 1.03 (1.00.1.20) g/L to 1.08 (1.00.1.22) g/L with the p-value of 0.044. Conclusion: Our findings suggest that the genetic variations of APOA1 rs5072 and APOA4 rs1268354 contribute to the susceptibility of SZ, and the expression levels of APOA1 and APOA4 mRNA of peripheral blood leukocytes decreased in SZ patients during the episode while APOA4 increased after antipsychotic treatment.

Red Blood Cell Morphological Changes and Enlarged Platelets Found in Idiopathic Multicentric Castleman Disease

BACKGROUNDIdiopathic multicentric Castleman disease (iMCD) is a rare polyclonal lymphoproliferative disorder characterized by systemic inflammatory symptoms, cytopenias, generalized lymphadenopathy, and multiple organ system dysfunction. iMCD is subclassified into iMCD-TAFRO, with thrombocytopenia, anasarca, fever/elevated C-reactive protein, reticulin myelofibrosis/renal failure, and organomegaly, and iMCD-NOS (not otherwise specified), with high platelet counts and hypergammaglobulinemia. Despite recent diagnostic guidelines, iMCD diagnosis remains challenging because many of the histopathologic features and clinical/laboratory abnormalities are non-specific. Characterization of easily measurable findings from minimally invasive procedures, such as peripheral blood smear, could help to improve the accuracy of diagnosis as well as potentially providing insights into disease pathogenesis. Peripheral blood smears are often performed during routine clinical evaluation and enable morphologic evaluation of red blood cells (RBCs) and white blood cells (WBCs). In this study, we systematically characterized peripheral blood smear morphologic findings in iMCD for the first time.METHODSPeripheral blood smear morphologic findings in medical records from 68 iMCD patients, who were enrolled in an international registry for CD patients and had been confirmed to meet iMCD criteria by an expert panel, were reviewed and analyzed. Patients were also categorized into iMCD-TAFRO (N=39) or iMCD-NOS (N=29) based on clinical and laboratory data. Two-sample proportion tests were used to compare the frequency of features between iMCD-TAFRO and iMCD-NOS, when the abnormality was present in ≥ 5 subjects in both subtypes. P-value correction was not performed as findings are preliminary and hypothesis generating.RESULTSAmong the 68 iMCD patients, average age was 35.8 years (14-61); 46% were female, 54% were male; racial distribution was 62% white; 10% Black; 15% Asian; 13% other. The most common peripheral blood smear findings across all iMCD patients included abnormalities in RBC size and color, with anisocytosis (58.8%), polychromasia (57.4%), hypochromia (55.9%), and microcytosis (50.0%) being the most prevalent findings in the overall cohort (Table 1). Other RBC abnormalities were observed but less frequently, including abnormalities in shape such as poikilocytosis (44.1%). Giant or large platelets were found in 47% of iMCD cases. Abnormalities in WBCs, including toxic granulation, atypical lymphocytes, and toxic vacuolization, were detected less frequently. When comparing the two clinical subtypes, patients with iMCD-TAFRO had more frequent anisocytosis (p=0.043), hypochromia (p=0.002), polychromasia (p=0.022), and giant/large platelets (p<0.001) versus iMCD-NOS.DISCUSSIONHere, we have characterized peripheral blood morphologic abnormalities in iMCD for the first time. The most common findings in this cohort included abnormalities in RBC size and color. These abnormalities can be found in a number of conditions, including myelofibrosis, autoimmune diseases, and other inflammatory conditions. In iMCD, they are likely related to cytokine-driven anemia of chronic inflammation. The presence of large or giant platelets in nearly half of iMCD patients, with significantly more in iMCD-TAFRO than iMCD-NOS, is particularly notable since this has not been described in iMCD. These enlarged platelets, which can be found in immune thrombocytopenic purpura, myeloproliferative disorders, pseudothrombocytopenia, and inherited platelet disorders, may reflect hyperactivity of megakaryocytes and/or early release from the bone marrow in response to peripheral platelet sequestration. Though less common in this cohort, there are additional changes in RBC shape and WBC features that may be more specific to iMCD and potentially informative in increasing the index of suspicion for iMCD. These findings suggest that the peripheral blood smear may be able to support the diagnosis of iMCD and result in faster treatment administration. Future work is needed to determine whether the constellation of findings in the peripheral blood identified herein is unique to iMCD or seen in various other infectious, malignant, and autoimmune diseases. [Display omitted] DisclosuresFajgenbaum: Pfizer: Other: Study drug for clinical trial of sirolimus; EUSA Pharma: Research Funding; N/A: Other: Holds pending provisional patents for ‘Methods of treating idiopathic multicentric Castleman disease with JAK1/2 inhibition’ and ‘Discovery and validation of a novel subgroup and therapeutic target in idiopathic multicentric Castleman disease’.

Accuracy and Efficacy of Software-guided Bony Realignment in Periarticular Deformities of the Lower Limb.

Aim and objectiveSoftware-guided realignment is proposed as an easy and accurate method of achieving simultaneous multiaxial correction. The accuracy and efficacy in periarticular problems have not been investigated fully. This study investigates the results and possible clinical benefits.Materials and methodsA retrospective review was performed in 24 patients with 27 periarticular deformities of the lower limb treated by the Ilizarov technique. Bony realignment was achieved by a software-guided hexapod realignment device. The deformity category, deformity severity score (DSS) and individual deformity component scores were measured for objective quantification of each deformity. The periarticular level, number of manoeuvres, correction period and any difficulties in the execution of the correction manoeuvre were noted. Pre-procedure and post-procedure values of deformity parameters were analysed to estimate the accuracy and efficacy of the realignment device.ResultsThe correction manoeuvre was accomplished successfully in all patients except two. The mean correction period was 14.9 days (range, 5–38 days). The mean pre-procedure DSS was 18.7 (range 6.3–27.3), which reduced to a mean post-procedure value of 1.5 (range, 0–7.9) with a 92.0% deformity correction (p-value < 0.001)). There was a significant reversal of individual deformity components. DSS values were achieved to an excellent level (< 3.5) in 25 deformities and to good and poor levels in one deformity, respectively.ConclusionSoftware-guided realignments are effective for accurate realignment of periarticular deformities using Ilizarov fixators. These devices offer simultaneous multidimensional corrections even in complex multiplanar deformities and simplify the task of deformity correction.Clinical significanceThe present study assesses the accuracy and efficacy of software-guided realignments using novel concepts of deformity category, DSS and individual deformity component scores, which may overcome some of the shortcomings of conventional assessment methods.How to cite this articleSingh P, Sabat D, Dutt S, et al. Accuracy and Efficacy of Software-guided Bony Realignment in Periarticular Deformities of the Lower Limb. Strategies Trauma Limb Reconstr 2021;16(2):65–70.

Integration analysis of GWAS and expression quantitative trait loci to identify candidate genes and pathways for clozapine-related neutropaenia.

Little is known about the genetic basis of clozapine-related neutropaenia. This study aims to explore candidate genes and pathways involved in clozapine-related neutropaenia. This study conducted a two-stage integrative analysis of the summary statistics from the genome-wide association study (GWAS, n = 552) of the lowest absolute neutrophil count (ANC) during clozapine treatment and the summary data of the expressed quantitative trait locus (eQTL). First, we use the probabilistic Mendelian randomization (PMR-Egger) to identify genes whose expression is causally related to ANC, and then use Bayesian co-localization analysis to investigate whether there are shared causal variants between them [posterior probability for hypotheses 4 (PP.H4) > 0.80]. Finally, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to explore the pathways that may be associated with ANC during clozapine treatment. PMR-Egger analysis identified 146 genes that may be causally associated with ANC after Bonferroni correction (P-value < 3.25e-6). Bayesian co-localization analysis identified six further genes whose gene expression shared common variants with ANC, including NT5E (PP.H4 = 0.96), GLDC (PP.H4 = 0.82), NUDT17 (PP.H4 = 0.88), MSH4 (PP.H4 = 0.88), PTER (PP.H4 = 0.89) and SERPINB6 (PP.H4 = 0.83). Enrichment analysis identified 52 GO terms and seven pathways associated with ANC, such as NAD metabolic process, drug catabolic process and glyoxylate and dicarboxylate metabolism. This study identified multiple candidate genes and pathways that may be involved in clozapine-related neutropaenia, providing novel clues for the mechanism of clozapine-related neutropaenia.

A non-parametric method to test the statistical significance in rolling window correlations, and applications to ecological time series

We provide a non-parametric computing-intensive method to test the statistical significance of the rolling window correlation for bi-variate time series. This method (test) addresses the effects due to the multiple testing (inflation of the Type I error) when the statistical significance is estimated for the rolling window correlation coefficients. We follow Telford and Polanco-Martínez to carry out the proposed method. The method is based on Monte Carlo simulations by permuting one of the variables (dependent) under analysis and keeping fixed the other variable (independent). We improve the computational time of this method to reduce the computation time (speedup was up to practically five times faster than the sequential method using 11 cores) through parallel computing. We compare the results obtained through the proposed method with two p-value correction methods frequently used (Bonferroni and Benjamini and Hochberg –BH) after being applied to synthetic and to real-life ecological time series. Our results show that the proposed method works roughly similar to these two p-value correction methods, especially with the method of BH, but our test is a little more restrictive than BH and a little more permissive than Bonferroni. The test is programmed in R and is included in the package NonParRolCor that is available freely on CRAN.

The likelihood-ratio test for multi-edge network models

The complexity underlying real-world systems implies that standard statistical hypothesis testing methods may not be adequate for these peculiar applications. Specifically, we show that the likelihood-ratio (LR) test’s null-distribution needs to be modified to accommodate the complexity found in multi-edge network data. When working with independent observations, the p-values of LR tests are approximated using a χ 2 distribution. However, such an approximation should not be used when dealing with multi-edge network data. This type of data is characterized by multiple correlations and competitions that make the standard approximation unsuitable. We provide a solution to the problem by providing a better approximation of the LR test null-distribution through a beta distribution. Finally, we empirically show that even for a small multi-edge network, the standard χ 2 approximation provides erroneous results, while the proposed beta approximation yields the correct p-value estimation.